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Diagnosis the Breast Cancer using Bayesian Rough Set Classifier

Breast cancer was one of the most common reasons for death among the women in the world. Limited awareness of the seriousness of this disease, shortage number of specialists in hospitals and waiting the diagnostic for a long period time that might increase the probability of expansion the injury cases. Consequently, various machine learning techniques have been formulated to decrease the time taken of decision making for diagnoses the breast cancer and that might minimize the mortality rate. The proposed system consists of two phases. Firstly, data pre-processing (data cleaning, selection) of the data mining are used in the breast cancer dataset taken from the University of California, Irvine machine learning repository in this stage we modified the Correlation Feature Selection (CFS) with Best First Search (BFS) established on the Discriminant Index (DI) so as to reduce the complexity of time and get high accuracy. Secondly, Bayesian Rough Set (BRS) classifier is applied to predict the breast cancer and help the inexperienced doctors to make decisions without need the direct discussion with the specialist doctors. The result of experiments showed the proposed system give high accuracy with less time of predication the disease.

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Publication Date
Mon Jan 28 2019
Journal Name
Iraqi Journal Of Science
Estimation of the relationship between the time delay of mastectomy and the stage of breast cancer among a group of infected Iraqi females

This study assesses the delay of mastectomy "time from the first consultation of a doctor to the time of mastectomy" and its relationship with the stage of the disease among Iraqi women with breast cancer. A study was carried out on (113) women who were referred to the Outpatient Clinic of the Oncology Teaching Hospital and the Iraqi National Cancer Research Center, University of Baghdad, for the period from 2012 to 2016.Patients' age range between (40-49) years comprised (60.2%) of cases, and showed advanced tumor stage (62.96%)of stage III. It was found that infiltrating ductal carcinoma was the most common type of breast cancer that found in (77%) of cases.

Mostly there was no delay of mastectomy for more than one month delay

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Publication Date
Wed Oct 28 2020
Journal Name
Iraqi Journal Of Science
Epileptic Seizures Detection Using DCT-II and KNN Classifier in Long-Term EEG Signals

     Epilepsy is one of the most common diseases of the nervous system around the world, affecting all age groups and causing seizures leading to loss of control for a period of time. This study presents a seizure detection algorithm that uses Discrete Cosine Transformation (DCT) type II to transform the signal into frequency-domain and extracts energy features from 16 sub-bands. Also, an automatic channel selection method is proposed to select the best subset among 23 channels based on the maximum variance. Data are segmented into frames of  one Second length without overlapping between successive frames. K-Nearest Neighbour (KNN) model is used to detect those frames either to ictal (seizure) or interictal (non-

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Publication Date
Tue Jun 01 2021
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Evaluation of Ceruloplasmin Oxidase Activity in Sera of Breast Cancer Individuals in Kurdistan Region/ Iraq

Ceruloplasmin is considered the main copper transport protein which is proposed to have a role in cancer. Ceruloplasmin is an acute phase reactant and antioxidant enzyme, has been found to be increased in sera of patients with several types of cancers including breast cancer.

The aim of present study was to determine of ceruloplasmin oxidase activity, specific activity, iron concentration in sera of patients with breast cancer and comparing with healthy group, and the ability of using enzyme as a tumor marker for breast cancer.

This study was performed from November 2018 to January 2019, blood samples were collected from breast cancer patients in Nanakeli Hospital in Erbil city. Study was included (65) female patients wit

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Advanced Pharmaceutical Technology & Research
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Publication Date
Mon Jul 06 2020
Journal Name
International Journal Of Research In Pharmaceutical Sciences
Obesity and Breast Cancer: Circulating Adipokines and Their Potential Diagnostic as Risk Biomarkers

Obesity and cancer are two major epidemics of this century. Obesity is related to a higher risk of many types of cancer. Studies have accessed circulating adipokines, as key-mediators in obesity and breast cancer. The study is aimed to examine the circulating levels of insulin-like growth factor-1, leptin, adiponectin, and resistin in premenopausal Iraqi women with breast cancer. The current study was performed during the period from June 2019 to December 2019 at Oncology unit/ Medical City Hospital-Baghdad. A total of 90 premenopausal women with BC/ stage II and III after 2nd dose of chemotherapy were contributed in this study as patients group. Their ages ranged from (35- 50) years in addition to 90 premenopausal healthy women wer

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Publication Date
Sun Dec 10 2017
Journal Name
Journal Of Pharmaceutical, Chemical And Biological Sciences
BRCA1 is Overexpressed in Breast Cancer Cell Lines and is Negatively Regulated by E2F6 in Normal but not Cancerous Breast Cells

This study focused on the expression and regulation of BRCA1 in breast cancer cell lines compared to normal breast. BRCA1 transcript levels were assessed by real time quantitative polymerase chain reaction (RT-qPCR) in the cancer cell lines. Our data show overexpression of BRCA1 mRNA level in all the studied breast cancer cell lines: MCF-7, T47D, MDA-MB-231 and MDA-MB-468 along with Jurkat, leukemia T-lymphocyte, the positive control, relative to normal breast tissue. To investigate whether a positive or negative correlation exists between BRCA1 and the transcription factor E2F6, three different si-RNA specific for E2F6 were used to transfect the normal and cancerous breast cell lines. Interestingly, strong negative relationship was found b

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Publication Date
Tue Jan 30 2024
Journal Name
Iraqi Journal Of Science
Effect of s-Klotho Protein, GPX, Visfatin, Leptin and ROS of Iraqi Women with Breast Cancer

     The most prevalent cancer is breast cancer, and the incidence of breast cancer in women worldwide is increasing at a remarkably rapid rate. This study was conducted on 90 samples (45 newly diagnosed breast cancer samples and 45 control group samples), ranging in age from 35 to 70 years. Blood samples were collected from the Alawia Teaching Hospital and the Oncology Teaching Hospital between October 2020 and March 2021. ELISA assessed ROS, GPX, visfatin, IGF-1, vitamin A, leptin, and soluble al-Klotho. The results indicate that the breast cancer patients had significantly higher (ROS 3.57, visfatin 17.44) (ng/mL) (p<0.0001) and leptin 16.11 (ng/mL). In the group of patients, there was a significant increase (p<0.004) compar

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Publication Date
Sat Oct 20 2018
Journal Name
Journal Of Economics And Administrative Sciences
Bayesian Tobit Quantile Regression Model Using Four Level Prior Distributions

Abstract:

      In this research we discussed the parameter estimation and variable selection in Tobit quantile regression model in present of multicollinearity problem. We used elastic net technique as an important technique for dealing with both multicollinearity and variable selection. Depending on the data we proposed Bayesian Tobit hierarchical model with four level prior distributions . We assumed both tuning parameter are random variable and estimated them with the other unknown parameter in the model .Simulation study was used for explain the efficiency of the proposed method and then we compared our approach with (Alhamzwi 2014 & standard QR) .The result illustrated that our approach

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Publication Date
Mon Oct 14 2019
Journal Name
Open Access Macedonian Journal Of Medical Sciences
Comparison of Clinico-Pathological Presentations of Triple-Negative versus Triple-Positive and HER2 Iraqi Breast Cancer Patients

BACKGROUND: Breast cancer remains the most common malignancy among the Iraqi population. Affected patients exhibit different clinical behaviours according to the molecular subtypes of the tumour. AIM: To identify the clinical and pathological presentations of the Iraqi breast cancer subtypes identified by Estrogen receptors (ER), Progesterone receptors (PR) and HER2 expressions. PATIENTS AND METHODS: The present study comprised 486 Iraqi female patients diagnosed with breast cancer. ER, PR and HER2 contents of the primary tumours were assessed through immunohistochemical staining; classifying the patients into five different groups: Triple Negative (ER/PR negative/HER2 negative), Triple Positive (ER/PR positive/HER2 positive), Luminal A (ER

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Publication Date
Mon Jan 01 2018
Journal Name
Research Journal Of Pharmacy And Technology
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